Performance Evaluation and Enhancement of Mobile Node: MIH

Performance Evaluation and Enhancement of Mobile Node: MIH PERFORMANCE EVALUATION AND ENHANCEMENT OF MOBILE NODE USING MIH CHAPTER 4 NETWORK SIMULATOR 4.1 Introduction NS2 is associate open-source simulation tool that runs on Linux, its a discreet event machine targeted at networking analysis and provides substantial support for simulation of routing, multicast protocols and informatics protocols, like UDP, TCP, RTP and SRM over wired and wireless (local and satellite) networks. Its several blessings that build it a great tool, like support for multiple protocols and therefore the capability of diagrammatically particularization network traffic. In addition, NS2 supports many algorithms in routing and queuing. Local routing and broadcasts are a part of routing algorithms. Queuing algorithms embody honest queuing, deficit round-robin and FIFO. NS is associate object oriented machine, written in C++, with associate OTcl interpreter as a frontend. The machine supports a category hierarchy in C++ (also referred to as the compiled hierarchy during this document), and an identical category hierarchy inside the OTcl interpreter (also referred to as the taken hierarchy during this document). The 2 hierarchy’s square measure closely associated with every other; from the user’s perspective, theres a matched correspondence between a category within the taken hierarchy and one within the compiled hierarchy, the basis of this hierarchy is that the category Tcl Object. Users produce new machine objects through the interpreter; these objects square measure instantiated inside the interpreter, and square measure closely reflected by a corresponding object within the compiled hierarchy. The taken category hierarchy is mechanically established through strategies outlined within the category TclClass. User instantiated objects square measure reflected through strategies outlined within the category TclObject. NS2 is extensively utilized by the networking analysis community. It provides substantial support for simulation of communications protocol, routing, multicast protocols over wired and wireless (local and satellite) networks, etc. The machine is event-driven and runs in a very non-real-time fashion. It consists of C++ core strategies and uses Tcl and Object Tcl shell as interface permitting the computer file (simulation script) to explain the model to simulate. Users will outline arbitrary network topologies composed of nodes, routers, links and shared media. A chic set of protocol objects will then be hooked up to nodes, sometimes as agents. The machine suite conjointly includes a graphical beholder referred to as network animator (NAM) to help the users get additional insights regarding their simulation by visualizing packet trace information. NS is an occasion driven network machine developed at UC Berkeley that simulates style of informatics networks. It implements network protocols like communications protocol and UPD, traffic supply behavior like FTP, Telnet, Web, cosmic microwave background and VBR, router queue management mechanism like Drop Tail, RED and CBQ, routing algorithms like Dijkstra, and more. NS conjointly implements multicasting and a few of the mac layer protocols for computer network simulations.    4.2 A Short History   NS2 started as a variant of the $64000 network machine in 1989 (see Resources). REAL could be a network machine originally supposed for the real the dynamic behavior of flow and congestion management schemes in packet-switched information networks. NS2 is associate degree object-oriented machine developed as a part of the VINT project at the University of American state in Berkeley. The project is funded by government agency together with XEROX Palo Alto research center (PARC) and Lawrence Berkeley National Laboratory (LBNL). NS2 is accessible on many platforms like Linux, Ubuntu, FreeBSD, SunOS and Solaris. NS2 conjointly builds and runs underneath Windows. Large scenarios benefit from large amounts of memory. Additionally, NS2 requires the following packages to run these scenarios Tcl has released Tcl8.3.2, Tk has released Tk 8.3.2, OTcl has released OTcl 1.0a7 and also TclCL has released TclCL 1.0b11. 4.3 C++ and OTCL Duality In this means, the controls of the C++ objects area unit given to OTcl. It’s conjointly attainable to feature member functions and variables to a C++ connected OTcl object. The objects in C++ that dont have to be controlled during a simulation or internally utilized by another object dont have to be connected to OTcl. Likewise, associate degree object (not within the information path) is entirely enforced in OTcl. Fig 4.1: C++ and OTcl: The Duality In this means, the controls of the C++ objects area unit given to OTcl. It’s conjointly attainable to feature member functions and variables to a C++ connected OTcl object. The objects in C++ that dont have to be controlled during a simulation or internally utilized by another object dont have to be connected to OTcl. Likewise, associate degree object (not within the information path) is entirely enforced in OTcl. Figure 5.1 shows associate degree object hierarchy example in C++ and OTcl. One factor to notice within the figure is that for C++ objects that have associate degree OTcl linkage forming a hierarchy, theres an identical OTcl object hierarchy terribly just like that of C++. NS was inbuilt C++ and provides a simulation interface through OTcl, associate degree object-oriented idiom of Tcl. The user describes a constellation by writing OTcl scripts, so the most ns program simulates that topology with mere parameters. The NS2 makes use of flat earth model within which it assumes that the atmosphere is flat with none elevations or depressions. But the real world will have geographical options like valleys and mountains.NS2 fails to capture this model in it. Many researchers have planned the additions of latest models to NS2.Shadowing Model in NS2 makes an attempt to capture the shadow impact of signals in real world, however will that inaccurately.NS2s shadowing model doesnt think about correlations: a true shadowing impact has sturdy correlations between 2 locations that area unit near one another. Shadow attenuation ought to be sculptured as a 2 dimensional log-normal random method with exponentially decaying spacial correlations. 4.4 Screenshot of Network Animator Fig 4.2: Network Animator Window NS animator window is shown in the above figure 4.2 which can be used to view the connection between the mobile and the network towers, it shows the movement packet drops which take place during simulation. 4.5  NIST’s Media Independent Handover module 4.5.1  Introduction Wireless network types Handover are off two types, Horizontal handovers also called Homogenous Handover and Vertical handovers also called Heterogeneous handovers. If Handover take place in same access technology (WiFi WiFi) or (WIMAXWIMAX) is Horizontal and if Handover takes place within the different access technology (WiFi WiMAX) or (WIMAXWIFI) is Vertical Handover. If Longer the handover duration, then higher the packet drop and poor QoS [7]. IEEE with 802.21 MIH addressed vertical handover, which separates the different access technology in a mobile device from the upper layers in the protocol stack. NIST has provided the 802.21 MIH add-on modules [3] for network simulator (ns2.29). These module support the two of the MIH functions, events and commands. 4.5.2  Supporting Technologies of 802.21 in ns-2 Ns-2.29 supports the access technologies in IEEE 802.21 scenarios are: WiMAX (802.16), Wi-Fi (802.11), UMTS and Ethernet (802.3). 4.5.3  Implementation of Nodes with Multiple Interfaces in ns-2 NS-2 does not support the heterogeneous multiple interfaces of a mobile node (MN), because node structure do not necessarily follow the same as the one defined in the basic model by external packages. Hence to resolve this issue, NIST add-on module created the concept of multiFace node also called super node, which is a mobile node which can links to other mobile nodes, these interfaces for the multiFace node, and the multiFace node can be viewed as as â€Å"supernode†. This concept is illustrated in Fig. 4.1. Fig. 4.1: High Level View of MultiFace Node Fig. 4.2: Power boundaries defined in NS2 The interface nodes activate the events and forwards them to the super node. The MIH Users on the super node are often ready to register and to receive these events. 4.5.4  Power Boundaries are often outlined in Wifi and WiMAX Cells In order to spot power boundaries which may be utilized in the simulation, 3 variables are outlined in ns-2.29, that is shown in Fig. 5.2. Theses variable are often outlined as: †¢CSTresh: accustomed outline the minimum power level to sense wireless packets and conjointly switch the mac layer, if mac layer is idle then it are often switched to busy, †¢RX Tresh: are often accustomed outline the minimum power level to receive wireless packets with error free; †¢pr_limit: are often perpetually equal or superior to one and is employed within the equation (RX Tresh) * (pr_limit), then this equation are going to be shaping the minimum power level that Associate in Nursing interface senses Link taking place event before triggering. In the above figure Fig 4.2, shows the ability boundaries between WLAN and WiMAX base station with its vary wherever the highest most layer is Cs thresh_, middle layer is rx thresh_ and also the inner layer is rx thresh_ * pr limit_. Dept. of CSE, VKIT 2014-20151 Education and Fertility | Literature Review Education and Fertility | Literature Review The relation between the education and fertility of women is a topic that has received much attention in the last decades. Some scholars have found that there is an inverse relation between the education and fertility, however, it is still unknown if this relation is causal or not. But in general, across countries, when women acquire more education, this decreases the number of children. The spread of education around the world has been linked to decreases in fertility that incremented women rates of enrollment and completion of secondary education. In point of fact, women with secondary education have on average one less child (Leà ³n, 2004). When estimating the relationship between education and fertility there are unobserved characteristics that affect schooling preferences and are correlated with unobserved variables that encourage to have a child or not. To better clarify this criteria, we have to analyze the next example. When a woman has wishes to work, attend college, make a professional career, this will impact negatively the number of children that she wants to have. On the contrary, women with access to the credit market, are more likely to have more years of education and also to children. As we observe, there is no only a negative relation between fertility and education, but it also may be positive (although is not common). In addition, when analyzing the effect of education on fertility we have to take into account the welfare policy consequences. When the total fertility rates decreases and the life expectancy increases, this may cause an ageing of the population. Therefore, the ratio of retirees to working-age adults increases and this create a serious problem on spending of governments on health care and pensions. This is the case of developed countries. By the contrary, in developing countries (specially Latin American countries), when the total fertility rate decreases, the risk of health between women and children decreases leading to a improvement in the welfare conditions. In the recent years, programs such as the World Banks Female Secondary Schooling Assistance Project seek to motivate the education of women around the world. Given these facts, the hypothesis than education affect fertility levels of women is valid. Not only the education of women affect their fertility rate, but also the marriage, which is delayed because women desires to enter to the labor market or to increase their education. The theoretical aspects concerning to the relation of fertility and education is very broad. In order to explain this relation with more accuracy it is important to analyze the studies of Barro and Becker (1988), Livi-Baci (1997) and Willis (1973). They agree in the fact that women with more education diminishes their fertility because of the increment in the cost of opportunity of time. Other models point out the wage of women as the main factor in explaining the cost of opportunity of childbearing. Montgomery and Trussel (1986) analyze the children as normal goods. Here and increment in the education of women produces an increment in the parents income, which lead to an increment in the spending of normal goods (children), dominating the wage effect. It is also important to analyze the models that explain the fertility as stochastic processes (Wolpin (1994), Newman (1988) and Hotz and Miller (1988), however, this studies have no provided any result about the empirical specification for the life cycle fertility. They just agree in the fact that the returns of more years of education are positive and that this produces an inverse relation between education and fertility in women. Reviewing the literature between education and fertility, we have to highlight the contribution of the studies done by Becker. Becker (1960) and Becker and Lewis (1973) analyze the child quality fertility model, which is one of the most used model in explaining the relation between education and fertility. This model analyze the role of income of parents in the quality and quantity of children. That is to say that when the income of parents increases, the quality and quality of children also increases. Becker argues that the income elasticity of the quantity of children is small related to the income elasticity of the quality of children. Given the fact that the spending on children increases, it leads to a prevalence of the higher quality. In this case, the substitution effects subdue to the income effect. Following this criteria, Easterlin and Crimmins (1985) formulates the theory of the demand of children, referring mainly to the desired family size of parents but taking into consideration that the knowledge of birth control instruments is general and does not imply any cost. Moreover, the supply of children refers to the quantity of children that parents would experience, without limiting the family size. As we can observe, all the theories mentioned above deal with the negative relation between fertility and education, just with the exception of the supply theory that connects the health and the fecundity. Therefore the role of education is very important given the fact that help women to have more knowledge about contraceptive methods, and gain different perspectives of life. In addition, according to the economic theory, the relation of education and fertility has consequences for the welfare policies of the countries. An analysis in Developing Countries The fertility rate has decreased in Latin American countries through the years. According to Weilti (1993) the industrialization and modernization have been drivers in this reduction. On the one hand, with the industrialization the technology, communication, infrastructure and transport was improved. On the other hand, modernization has had a greater impact on fertility, improving of health care, education, urbanization. The arguments in explaining the decrement in fertility are mainly two: gender equality and education of women. Gender equality refers to the control of women on their lives (in all aspects) and education promote all of this independence of women. In recent years the inquiry about if educated women are selected for additional features that could be related to lower fertility such as income, earning of husband has brought lot of discussion. All of these additional features including on the analysis appears to be as indicators of a negative relation between fertility and education. Also it is important to mention that the autonomy of women is an important aspect when decreasing their fertility (Dyson and Moore, 1983). This implies that educated women has more independence in taking decisions in their life ((Basu (1992); Morgan and Niraula (1995); Vlassoff (1996)). The literature about the negative relation between fertility and education is very broad. Currently, there is lot of discussion about the reduction on mortality and the increasing aspirations from the women as main factors in explaining this relation. The decrease in fertility according to demographers is explained by reductions in infant and child mortality. The increasing aspirations of women is another important factor in explaining the negative relation between education and fertility. This model, that relates the decreasing in fertility levels with the increasing in aspirations of women, tries to explain mainly the resources in the market that women spend in children and in goods and this decision on how much to spend in each thing depend on preferences of women. According to the DHS survey carried out in the 80s, one of the most powerful tools of fertility is the access to mass media in developing countries, especially when talking about contraceptive methods and family size. The access to mass media it is really important in the family planning of households. But according to some authors as (Ramesh et al. (1996, Westoff and Rodriguez (1995) the education should increase along with the increase of the material aspirations. As reductions in fertility (at macro-level) are given by increments in educational, we expect that education has a connection with rising aspirations (United Nations, 1995). In fact, in South Asia, accoring to Basu (1999), the decrease in fertility is linked to increments in dowry. As we can observe, the relation between education and fertility seems to be explained with the theory about material aspirations of women. Following this theory of the material aspirations of women, we come to the conclusion that the increment in material aspirations and more investments in the schooling of daughters can provoke a decline in fertility in the couple. The impact on Latin American Countries According to the International Family Planning Perspectives, 21:52-57 80, 1995), women that have no education have on average bigger families of 6 or 7 children, while women that have education 2 or 3 children. The knowledge about contraceptive methods is more favorable to educated women (Demographic and Health Surveys for 9 Latin American countries). It is important to point out that the negative relation between education and fertility stopped being as an automatic progress after the World Fertility Survey in the 70s when the results gave a broader idea that the fertility reductions are explained by the development, gender stratification of the society. The impacts of education on fertility can be explained for the following aspects. In first place, the education acts as a source of knowledge, given the fact that schooling improves the knowledge of women about different lifestyles and a major access to information about fertility elections. Secondly, education is a tool for the development of a country. The education is a cover letter to entry formally to the labor market. And finally the education acts as a transformer of attitudes, specially aspirations in life. It is known that Latin American is the most unequal society in the world. The gap between the rich and poor people has increased in the last years and this situation seems to not come to an end. In some Latin American Countries the access to a good education is given mainly by the social origins. Not always, but in most of cases, poor people has no access to an education because of the lack of money and opportunities. But this situation has improved in the last decades with the free access to public education and improvements in the literacy rates of Latin American Countries. However, in countries such as Guatemala, 42% of women have no formal education (Indicators of female educational attainment in Latin America, by country, 1985-1989). As we observe in the table below, the 1/5 of the people in Bolivia and El Salvador has no education, which is a extremely bad indicator. In the rest of the Latin American countries the years of schooling show a better performance, reaching 10 years of education roughly. As we mentioned above, the improvements in education has been a major concern in Latin American Governments in the recent decade. As we observe in the table, countries such as Colombia, Peru, Ecuador, Dominican Republic and Mexico has showed substantial progress in the school attendance (1.4, 1.7, 1.4, 2.2. and 3.4 years respectively). The relation between fertility and education in Latin American is considered as the most powerful in the world. This is explained by the differential in reproductive strategies inside this society. If we refer to pretransitional societies, the behavior of women with no education is similar to the one of that societies, having on average 6 or 7 children, while women with better education have on average 2 or 3 children. In table 2, there is a surprising fact in which the fertility patterns (desired family size) are almost the same among poor (educated) women and educated women, but in practice they differ a lot. Referring to the contraceptive knowledge, here we find a big difference. The difference between uneducated and educated women in Colombia and Dominic Republic is 20% and 40% in Bolivia, Ecuador, Peru and Mexico.